Exploration of linear and interpretable models for quantification of cell parameters via contactless short-wave infrared hyperspectral sensing by Anjana Hevaganinge, Eva Lowenstein, Anna Filatova, Mihir Modak, Nandi Thales Mogo, Bryana Rowley, Jenny Yarmowsky, Joshua Ehizibolo, Ravidu Hevaganinge, Amy Musser, Abbey Kim, Anthony Neri, Jessica Conway, Yiding Yuan, Maurizio Cattaneo, Sui Seng Tee, Yang Tao

“…Using only 50% of the dataset for training, reasonable test performance of mean absolute error (MAE) and correlations (r2) are achieved for glucose (r2 = 0.88, MAE = 37 mg/dL), lactate (r2 = 0.93, MAE = 15.08 mg/dL), and VCD (r2 = 0.81, MAE = 8.6 × 105 cells/mL). …”
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More is not always better: delta-downscaling climate model outputs from 30 to 5 min resolution has minimal impact on coherence with Late Quaternary proxies by L. Timbrell, L. Timbrell, J. Blinkhorn, J. Blinkhorn, M. Colucci, M. Colucci, M. Leonardi, M. Leonardi, M. Chevalier, A. V. Pozzi, M. Grove, E. Scerri, E. Scerri, E. Scerri, A. Manica

“…Optimal spatial resolution is therefore likely to be highly dependent on specific research contexts and questions, with careful consideration required regarding the trade-off between highlighting local-scale variations and increasing potential error via unreliable interpolation.</p>…”
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Improved Photosynthetic Accumulation Models for Biomass Estimation of Soybean and Cotton Using Vegetation Indices and Canopy Height by Jinglong Liu, Jordi J. Mallorqui, Albert Aguasca, Xavier Fàbregas, Antoni Broquetas, Jordi Llop, Mireia Mas, Feng Zhao, Yanan Wang

“…Both Monte Carlo simulations and theoretical error propagation analyses indicate a maximum deviation percentage of approximately 20% for both crops, which is considered acceptable given the expected inter-annual variation in model transferability. …”
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Perancangan Software As A Service (SAAS) untuk Sistem Pelayanan Kesehatan Ibu dan Anak (PKIA) pada Puskesmas Se-Kota Mataram Berbasis Cloud Computing by Andy Hidayat Jatmika, Royana Afwani, Nadiyasari Agitha

“…The problems that arise from public health centers are: a long service process which includes patient data collection and patient data retrieval, and the number of errors in the processing of patient data, such as registration data, examination data, and referral data. …”
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Network Meta-Analysis of Factors Influencing the Carbon Sink Capacity of Urban Park Green Spaces by Yutong JI, Tianyi LIN, Lian LIU, Xiong LI

“…Additionally, heterogeneity, bias, and errors are examined through subgroup analyses based on park scale (a), functional characteristics (b), and climatic conditions (c), accompanied by the evaluation of publication bias using funnel plots.ResultsThe analysis in this research involves 50 eligible literature articles published between 2000 and 2024, which are selected from a total of 952 articles initially collected. …”
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A comparison of frequentist and Bayesian approaches to the Personalised Randomised Controlled Trial (PRACTical)—design and analysis considerations by Holly Jackson, Yiyun Shou, Nur Amira Binte Mohamed Azad, Jing Wen Chua, Rebecca Lynn Perez, Xinru Wang, Marlieke E. A. de Kraker, Yin Mo

“…The performance measures were: probability of predicting the true best treatment, and novel proxy variables for power (probability of interval separation) and type I error (probability of incorrect interval separation). …”
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Root zone soil moisture mapping at very high spatial resolution using radar-derived surface soil moisture product by Nadia Ouaadi, Abdelghani Chehbouni, Emna Ayari, Bouchra Ait Hssaine, Jamal ElFarkh, Michel Le Page, Salah Er-Raki, Aaron Boone

“…The results show that the approach performs reasonably well using Sentinel-1 SSM product with correlation coefficient (R) between 0.3 and 0.82, root-mean-square error (RMSE) between 0.05 and 0.12 m3/m3 and a bias in the range −0.1–0.07 m3/m3, at 15–20 cm depth. …”
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Development of low-cost handheld soil moisture sensor for farmers and citizen scientists by Siddhesh Mane, Gurjeet Singh, Narendra N. Das, Narendra N. Das, Anant Kanungo, Nishit Nagpal, Michael Cosh, Younsuk Dong

“…For generalized calibration in mineral soils, we observed an overall Root Mean Square Error (RMSE) of 0.035 m3m−3 and a bias of &lt;0.001 m3m−3 along with a strong correlation (R = 0.90). …”
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Hierarchical GraphCut Phase Unwrapping Based on Invariance of Diffeomorphisms Framework by Xiang Gao, Xinmu Wang, Zhou Zhao, Junqi Huang, Xianfeng David Gu

“…Experimental results demonstrate a 45.5&#x00D7; speedup and lower <inline-formula><tex-math notation="LaTeX">$L^{2}$</tex-math></inline-formula> error in both real experiments and simulations, showing potential for real-time applications.…”
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Research on Monitoring Nitrogen Content of Soybean Based on Hyperspectral Imagery by Yakun Zhang, Mengxin Guan, Libo Wang, Xiahua Cui, Yafei Wang, Peng Li, Shaukat Ali, Fu Zhang

“…The results show the following: (1) Soybean canopy spectral reflectance was highly significantly negatively correlated with soybean canopy nitrogen content in the range of 450–729 nm, and highly significantly positively correlated in the range of 756–774 nm, with the largest positive correlation coefficient of 0.2296 at 765 nm and the largest absolute value of negative correlation coefficient of −0.8908 at 630 nm. (2) The predictive model for soybean canopy nitrogen content based on three optimal spectral indices, NDSI(R₅₅₂,R₅₅₅), RSI(R₅₃₇,R₅₇₃), and DSI(R₅₄₀,R₅₅₅), was optimal, with R² of 0.9063 and 0.91566 and RMSE of 3.3229 and 3.2219 for the calibration and prediction set, respectively. (3) Based on the established optimal prediction model for soybean canopy nitrogen content combined with the UAV hyperspectral image data, spatial distribution maps of soybean nitrogen content at the flowering and seed filling stages were generated, and the R² between soybean nitrogen content in the spatial distribution map and the ground measured value was 0.93906, the RMSE was 3.6476, and the average relative error was 9.5676%, which indicates that the model had higher prediction accuracy and applicability. (4) The overall results show that the optimal prediction model for soybean canopy nitrogen content established based on hyperspectral imaging data has the characteristics of few parameters, a simple structure, and strong applicability, which provides a new method for realizing rapid, dynamic, and non-destructive monitoring of soybean nutritional status on the regional scale and provides a decision-making basis for precision fertilization management during soybean growth.…”
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ViTAU: Facial paralysis recognition and analysis based on vision transformer and facial action units by Jia GAO, Wenhao CAI, Junli ZHAO, Fuqing DUAN

“…By optimizing the mean squared error between the predicted and actual heatmaps, we can effectively identify the affected paralysis areas. …”
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Critical raw material-free multi-principal alloy design for a net-zero future by Swati Singh, Mingwen Bai, Allan Matthews, Saurav Goel, Shrikrishna N. Joshi

“…The Cuckoo Search Optimization (CSO) method produced reduced-CRM MPEAs that closely matched Thermo-Calc predictions, with an error margin below ± 20%. To assess the efficacy of these reduced-CRM MPEAs, we compared the hardness of newly synthesized MPEA with CRM-containing counterparts reported in the literature, particularly those with high-risk critical raw materials like Niobium (Nb) and Tantalum (Ta). …”
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Positioning control of DC servomotor-based antenna using PID tuned compensator by Eze P. C., Ugoh C. A., Inaibo D. S.

“…Direct current (DC) servomotor-based parabolic antenna is automatically positioned using control technique to track satellite by maintaining the desired line of sight for quality transmission and reception of electromagnetic wave signals in telecommunication and broadcast applications. With several techniques proposed in the literature for parabolic antenna position control, there is still a need to improve the tracking error and robustness of the control system in the presence of disturbance. …”
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Hybrid LSTM–Transformer Architecture with Multi-Scale Feature Fusion for High-Accuracy Gold Futures Price Forecasting by Yali Zhao, Yingying Guo, Xuecheng Wang

“…It also provides an interpretable hybrid framework for derivative pricing intelligence. Future applications could leverage high-frequency data sharing and cross-market risk contagion models to enhance China’s influence in global gold pricing governance.…”
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Monitoring irrigated dryland in China from 2000 to 2015 by integrating time series vegetation indices and environmental factors by Zijuan Zhu, Lijun Zuo, Zengxiang Zhang, Yun Shao, Haijun Bao, Xiaoli Zhao, Xiao Wang, Shunguang Hu, Sisi Yu, Tianshi Pan, Ziyuan Liu

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Continuous Estimation of Hand Kinematics From Electromyographic Signals Based on Power-and Time-Efficient Transformer Deep Learning Network by Chuang Lin, Chunxiao Zhao, Jianhua Zhang, Chen Chen, Ning Jiang, Dario Farina, Weiyu Guo

“…When tested on 38 subjects of the Ninapro DB2, the proposed model resulted in a correlation coefficient of <inline-formula> <tex-math notation="LaTeX">$0.82~\pm ~0.04$ </tex-math></inline-formula>, root mean squared error (RMSE) of <inline-formula> <tex-math notation="LaTeX">$10.77~\pm ~1.48$ </tex-math></inline-formula>, and normalized RMSE of <inline-formula> <tex-math notation="LaTeX">$0.11~\pm ~0.01$ </tex-math></inline-formula>, which were all similar to the results achieved by the state-of-the-art (SOTA) reference methods. …”
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High Spatial Resolution U-Pb Dating of Low-Uranium Calcite Using LA-MC-ICP-MS by Chenxi ZHANG, Yuxin XIONG, Jiali FU, Wei ZHAO, Lei SHU, Zengsheng LI, Jun XU, Changxiang ZHOU, Fei HONG

“…Samples LD-5, PTKD-2 and TARIM yielded a lower intercept age of 73.20±0.56Ma, 152.7±2.5Ma and 206.2±1.3Ma, respectively, under the condition of 44μm beam spot, which were in agreement with the calibrated results of ID-TIMS/ID-MC-ICP-MS within the error range. The BRIEF REPORT is available for this paper at http://www.ykcs.ac.cn/en/article/doi/10.15898/j.ykcs.202403160057.…”
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Biomarker and clinical data–based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal st... by Eva María Arriero-País, María Auxiliadora Bajo-Rubio, Roberto Arrojo-García, Pilar Sandoval, Guadalupe Tirma González-Mateo, Patricia Albar-Vizcaíno, Gloria del Peso-Gilsanz, Marta Ossorio-González, Pedro Majano, Manuel López-Cabrera, Gloria del Peso-Gilsanz

“…PD outcomes were analysed in four categories (endurance, exit from PD, cause of PD end, technical failure) by using MMT biomarkers in effluents and clinical databases.Results MMT biomarkers and clinical data can predict PD with a mean absolute error of 16.99 months by using an Extra Tree (ET) regressor. …”
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MOIRA-UNIMORE Bearing Data Set for Independent Cart Systems by Abdul Jabbar, Marco Cocconcelli, Gianluca D’Elia, Davide Borghi, Luca Capelli, Jacopo Cavalaglio Camargo Molano, Matteo Strozzi, Riccardo Rubini

“…Vibration signals were collected using sensors placed along the track, alongside key system variables such as cart position, following error, speed, and set current. Experiments were conducted under a wide range of operating conditions, including different fault types, fault severities, cart speeds, and fault orientations, for both single-cart and multi-cart configurations. …”
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First performance evaluation of easyPET.3D, a high-resolution and cost-effective benchtop preclinical PET scanner by Fabiana M. Ribeiro, Pedro M. C. C. Encarnação, Ana L. M. Silva, Pedro M. M. Correia, Afonso X. Pinto, Regina G. Oliveira, José Sereno, Mariana Lapo Pais, Antero Abrunhosa, Ismael F. Castro, Ana C. Santos, João F. C. A. Veloso

“…Conclusion EasyPET.3D geometry favours the reduction of parallax error, despite its low sensitivity. The system linearity is suitable for the low range of activities (7–8 MBq) used for mice imaging. …”
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